Staff ML Scientist: Ranking & Personalization (Remote)
Depop
Greater London
Hybrid
GBP 70,000 - 95,000
Full time
14 days+
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Benefits offered by this job
PMI and cash plan healthcare access
Subsidised counselling and coaching
Cycle to Work scheme
25 days annual leave
Flexible working options
18 weeks paid parental leave
Life Insurance
Job summary
A leading circular fashion marketplace is seeking a Staff ML Scientist to join their Ranking ML team in the UK. This role involves leading the design and deployment of advanced ranking algorithms, working collaboratively across various teams to deliver innovative solutions. Candidates should have significant experience in machine learning, especially in learning-to-rank models, and be proficient in Python along with ML frameworks like PyTorch or TensorFlow. Join us to drive impactful initiatives and mentor others in a dynamic work environment.
Qualifications
Significant experience as a Machine Learning Scientist with measurable impact.
Experience in designing learning-to-rank models.
Deep understanding of machine learning concepts.
Ability to productionize ML models from prototyping to deployment.
Advanced programming skills in Python.
Responsibilities
Lead design and deployment of advanced ranking models.
Collaborate with product, engineering, and data teams.
Manage end-to-end lifecycle of ML projects.
Research and integrate emerging ML techniques.
Mentor and coach team members.
Skills
Machine Learning
Python
Communication
Mentoring
Tools
PyTorch
TensorFlow
Job description
A leading circular fashion marketplace is seeking a Staff ML Scientist to join their Ranking ML team in the UK. This role involves leading the design and deployment of advanced ranking algorithms, working collaboratively across various teams to deliver innovative solutions. Candidates should have significant experience in machine learning, especially in learning-to-rank models, and be proficient in Python along with ML frameworks like PyTorch or TensorFlow. Join us to drive impactful initiatives and mentor others in a dynamic work environment.